Volume 7 Issue 5
Nov.  2018
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Article Navigation >  Journal of Radars  > 2018  >  7(5): 575-584
Luo Ying, Gong Yishuai, Chen Yijun, Zhang Qun. Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar[J]. Journal of Radars, 2018, 7(5): 575-584. doi: 10.12000/JR18035
Citation: Luo Ying, Gong Yishuai, Chen Yijun, Zhang Qun. Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar[J]. Journal of Radars, 2018, 7(5): 575-584. doi: 10.12000/JR18035
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Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar

DOI: 10.12000/JR18035
  • ①.

    Institute of Information and Navigation, Air Force Engineering University, Xi’an 710077, China

  • ②.

    Troop of No. 95561, PLA, Lasa 850000, China

  • ③.

    College of Information Engineering, Engineering University of CAPF, Xi’an 710086, China

Funds:  The National Natural Science Foundation of China (61571457, 61631019)
  • Received Date: 2018-04-25
  • Rev Recd Date: 2018-06-02
  • Publish Date: 2018-10-28
    Abstract
  • The micro-motion feature is one of the important characteristic information of spatial target recognition. However, the existing multifunctional Multi-Input Multi-Output (MIMO) radar usually has to allocate a large number of continuous time resources for target micro-motion feature extraction after target searching and tracking, which leads to a low real-time performance of target recognition and poor overall performance of radar system. To solve this problem, this paper presents a multi-target micro-motion feature extraction method for MIMO radar based on tracking pulses. First, according to the azimuth information of each target, the MIMO radar transmitting waveform is designed, and the tracking pulses are transmitted simultaneously for targets with different directions. On this basis, by considering the micro-motion feature extraction performance and the target tracking performance synthetically, the transmission time series of the tracking pulses are optimized. Finally, the narrowband tracking pulses are directly used to simultaneously extract the micro-motion features of the targets in different directions, which makes it no longer necessary to allocate additional radar resources for target feature extraction. Consequently, the real-time recognition performance and the working efficiency of radar are improved significantly. Simulations demonstrate that when the signal-to-noise ratio is larger than –10 dB, the micro-motion features of multi-targets can be extracted accurately, which verifies the effectiveness and robustness of the proposed method.

     

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    • References(18)
  • [1]
    Zhang Q, Luo Y, and Chen Y A. Micro-Doppler Characteristics of Radar Targets[M]. Jonathan Simpson, United Kingdom: Elsevier Science, 2016: 4–6.
    [2]
    杨琪, 邓彬, 王宏强, 等. 太赫兹雷达目标微动特征提取研究进展[J]. 雷达学报, 2018, 7(1): 22–45. DOI: 10.12000/JR17087

    Yang Qi, Deng Bin, Wang Hong-qiang, et al. Advancements in research on micro-motion feature extraction in the terahertz region[J]. Journal of Radars, 2018, 7(1): 22–45. DOI: 10.12000/JR17087
    [3]
    陈小龙, 董云龙, 李秀友, 等. 海面刚体目标微动特征建模及特性分析[J]. 雷达学报, 2015, 4(6): 630–638. DOI: 10.12000/JR15079

    Chen Xiao-long, Dong Yun-long, Li Xiu-you, et al. Modeling of micromotion and analysis of properties of rigid marine targets[J]. Journal of Radars, 2015, 4(6): 630–638. DOI: 10.12000/JR15079
    [4]
    冯存前, 李靖卿, 贺思三, 等. 组网雷达中弹道目标微动特征提取与识别综述[J]. 雷达学报, 2015, 4(6): 609–620. DOI: 10.12000/JR15084

    Feng Cun-qian, Li Jing-qing, He Si-san, et al. Micro-Doppler feature extraction and recognition based on netted radar for ballistic targets[J]. Journal of Radars, 2015, 4(6): 609–620. DOI: 10.12000/JR15084
    [5]
    Chen V C, Li F, Ho S S, et al. Micro-Doppler effect in radar: Phenomenon, model, and simulation study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 2–21.
    [6]
    Bai X R, Zhou F, and Bao Z. High-resolution three-dimensional imaging of space targets in micromotion[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(7): 3428–3440. DOI: 10.1109/JSTARS.2015.2431119
    [7]
    Li G and Varshney P K. Micro-Doppler parameter estimation via parametric sparse representation and pruned orthogonal matching pursuit[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(12): 4937–4948. DOI: 10.1109/JSTARS.2014.2318596
    [8]
    Du L, Ma Y Y, Wang B S, et al. Noise-robust classification of ground moving targets based on time-frequency feature from micro-Doppler signature[J]. IEEE Sensors Journal, 2014, 14(8): 2672–2682. DOI: 10.1109/JSEN.2014.2314219
    [9]
    牛杰, 刘永祥, 秦玉亮, 等. 一种基于经验模态分解的锥体目标雷达微动特征提取新方法[J]. 电子学报, 2011, 39(7): 1712–1715

    Niu Jie, Liu Yong-xiang, Qin Yu-liang, et al. A new method of radar micro-motion feature extraction of cone target based on empirical mode decomposition[J]. Acta Electronica Sinica, 2011, 39(7): 1712–1715
    [10]
    何其芳, 张群, 罗迎, 等. 正弦调频Fourier-Bessel变换及其在微动目标特征提取中的应用[J]. 雷达学报, 待出版. DOI: 10.12000/JR17069

    He Qi-fang, Zhang Qun, Luo Ying, et al. A sinusoidal frequency modulation Fourier-Bessel transform and its application to micro-Doppler feature extraction[J]. Journal of Radars, in press. DOI: 10.12000/JR17069
    [11]
    Li J and Stoica P. MIMO radar with colocated antennas[J]. IEEE Signal Processing Magazine, 2007, 24(5): 106–114. DOI: 10.1109/MSP.2007.904812
    [12]
    Ma C Z, Yeo T S, Liu Z F, et al. Target imaging based on l1l0 norms homotopy sparse signal recovery and distributed MIMO antennas[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(4): 3399–3414. DOI: 10.1109/TAES.2015.140939
    [13]
    Li J, Stoica P, and Zheng X Y. Signal synthesis and receiver design for MIMO radar imaging[J]. IEEE Transactions on Signal Processing, 2008, 56(8): 3959–3968. DOI: 10.1109/TSP.2008.923197
    [14]
    李慧, 赵永波, 程增飞. 基于线性调频时宽的MIMO雷达正交波形设计[J]. 电子与信息学报, 2018, 40(5): 1151–1158. DOI: 10.11999/JEIT170426

    Li Hui, Zhao Yong-bo, and Cheng Zeng-fei. MIMO radar orthogonal waveform set design based on chirp durations[J]. Journal of Electronics&Information Technology, 2018, 40(5): 1151–1158. DOI: 10.11999/JEIT170426
    [15]
    李玉翔, 任修坤, 孙扬, 等. 一种循环迭代的宽带MIMO雷达正交稀疏频谱波形设计方法[J]. 电子与信息学报, 2017, 39(4): 953–959. DOI: 10.11999/JEIT160597

    Li Yu-xiang, Ren Xiu-kun, Sun Yang, et al. Cyclic iterative method for wideband MIMO radar orthogonal sparse frequency waveform design[J]. Journal of Electronics&Information Technology, 2017, 39(4): 953–959. DOI: 10.11999/JEIT160597
    [16]
    Mallat S G and Zhang Z F. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12): 3397–3415. DOI: 10.1109/78.258082
    [17]
    Chen Y J, Zhang Q, Ma C Z, et al. Micromotion feature extraction of radar target using tracking pulses with adaptive pulse repetition frequency adjustment[J]. Journal of Applied Remote Sensing, 2014, 8(1): 083569. DOI: 10.1117/1.JRS.8.083569
    [18]
    叶淋美. 基于压缩感知的雷达信号处理应用研究[D]. [硕士论文], 厦门大学, 2014: 17–34.

    Ye Lin-mei. Study on application of compressive sensing in radar signal processing[D]. [Master dissertation], Xiamen University, 2014: 17–34.
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